一種基于多源數(shù)據(jù)的干旱事件監(jiān)測(cè)方法

doi:10.12306/2025jms.0004

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一種基于多源數(shù)據(jù)的干旱事件監(jiān)測(cè)方法
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                        10.12306/2025jms.0004
                    
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中圖分類(lèi)號(hào):P426.616;P412
基金項(xiàng)目:江蘇省氣象局青年基金資助項(xiàng)目(KQ202009);江蘇省氣象局面上資助項(xiàng)目(KM202010;KM202207)

A method for monitoring drought events using multi-source data

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摘要:

干旱對(duì)社會(huì)的經(jīng)濟(jì)發(fā)展有諸多不利影響,利用遙感技術(shù)及時(shí)掌握干旱發(fā)生及發(fā)展動(dòng)態(tài),對(duì)政府提高抗災(zāi)減災(zāi)能力有十分重要的意義。目前,多數(shù)干旱遙感研究利用的影響因素較為單一,缺乏對(duì)多源數(shù)據(jù)的融合應(yīng)用。本文在評(píng)估微波遙感數(shù)據(jù)ESA CCI_SM(European Space Agency Climate Change Initiative Soil Moisture)產(chǎn)品質(zhì)量的基礎(chǔ)上,結(jié)合日蒸散發(fā)差指數(shù)(Daily Evapotranspiration Deficit Index,DEDI)及降水量數(shù)據(jù),分別構(gòu)建了多元線性回歸模型和徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)(Radial Basis Function Neural Networks,RBFNN)模型,并將其與江蘇省14個(gè)農(nóng)業(yè)氣象觀測(cè)站的實(shí)測(cè)土壤濕度進(jìn)行了對(duì)比評(píng)估。結(jié)果表明:ESA CCI_SM 產(chǎn)品能在一定程度反映江蘇土壤水分變化。在考慮多種干旱相關(guān)因素影響的情況下,多元線性回歸模型及RBFNN模型對(duì)于監(jiān)測(cè)土壤水分的準(zhǔn)確率相較于ESA CCI_SM 產(chǎn)品本身均有不同程度的提高。其中,RBFNN模型對(duì)于研究區(qū)的干旱監(jiān)測(cè)更為敏感,干旱預(yù)警監(jiān)測(cè)適用性更高。結(jié)合2019年夏秋連旱事件,研究進(jìn)一步證明RBFNN模型能較為準(zhǔn)確地反映出旱情的發(fā)生發(fā)展。以上結(jié)果表明,RBFNN模型可為旱災(zāi)的遙感監(jiān)測(cè)提供一種新的方法。

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Drought has many adverse effects on social and economic development. Using remote sensing technology to timely grasp the occurrence and development of drought is of great significance for the government to improve the ability of disaster resistance and mitigation. At present, the influencing factors used in most drought remote sensing researches are relatively single, lacking the fusion application of multi-source data. Based on the evaluation of the microwave remote sensing data product quality from ESA CCI_SM (European Space Agency Climate Change Initiative Soil Moisture), this study integrated the Daily Evapotranspiration Deficit Index (DEDI) and precipitation data to construct both a multiple linear regression model and a Radial Basis Function Neural Network (RBFNN) model,which were then comparatively evaluated against in-situ soil moisture measurements from 14 agrometeorological stations in Jiangsu province. Results show that the ESA CCI_SM products can reflect the changes of soil moisture in Jiangsu province to a certain extent. Considering various drought related factors, the accuracy of monitoring soil moisture using multiple linear regression model and RBFNN model was improved to varying degrees compared to the ESA CCI_SM product itself. Among them, the RBFNN model was more sensitive to drought monitoring in the study area and showed higher applicability for drought warning and monitoring. Combined with the continuous drought events in summer and autumn in 2019, this study further shows that the RBFNN model can accurately reflect the occurrence and development of drought. The above results indicate that the RBFNN model could provide a new method for drought monitoring with remote sensing.

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李菁,姜有山,沈澄,李聰,王珂清,戴竹君.一種基于多源數(shù)據(jù)的干旱事件監(jiān)測(cè)方法.氣象科學(xué),2025,45(3):385-392 LI Jing, JIANG Youshan, SHEN Cheng, LI Cong, WANG Keqing, DAI Zhujun. A method for monitoring drought events using multi-source data. Journal of the Meteorological Sciences,2025,45(3):385-392

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收稿日期:2022-07-13
最后修改日期:2023-12-13
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在線發(fā)布日期: 2025-08-30
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